Spoofing URL Detection
Prema Bhushan Sahane, Sandhya Shelke, Rutuja Dhokane, Ketan Urkudkar, Omkar Dhawale · 2022
Currently, the range and severity of network information insecurity threats are quickly expanding. The most common ways which are deployed by hackers are to target end-to-end technology and exploit human weaknesses. Social engineering, spoofing are examples of these approaches.One approach in carrying out these attacks is to mislead the user using malicious Uniform Resource Locators (URLs). It’s tough to find harmful Uniform Resource Locators (URLs) but fascinating issue since phishers typically produce URLs at random and researchers must detect them while keeping in mind the behaviors underlying the generated spoofing URLs. This study discusses approaches for identifying Spoofing Web sites using Machine Learning techniques to analyze different aspects of benign and spoofing URLs. We examine how address bar-based features, anomalous characteristics, and HTMLand Java-based elements may be used to detect spoofing websites.